texture op• Data kinds: image → image
• Call: fullseye.apply(img, "sk_gabor", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: gen_gabor (the HALCON reference is a useful guide to its meaning and parameters)
*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
*The output is shown in a viridis-like pseudo-colour (dark purple = low, yellow = high) so that a field of quantities — distance, phase, orientation, depth — can be read.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ sk_gabor: knob a sweep (docs site)
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ sk_gabor: other inputs (docs site)
*The 4th column is a colour (H,W,3) input. This op handles colour without crossing channels (it does not convolve the colour channel as a third spatial axis).*
Gabor filter response magnitude. A classic feature extractor that convolves a sinusoidally modulated Gaussian kernel and responds strongly to texture with a specific spatial frequency and orientation.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の gen_gabor(Generate a Gabor filter.)に相当(近似。カーネル生成ではなく畳み込み結果を返す)。実装は `filters.gabor(v, frequency=0.1+0.3*a) の実部(戻り値の 1 番目、虚部は捨てている)を絶対値化して正規化したもの —— a は周波数を 0.1〜0.4 に振る。方向 theta` は既定の 0(水平方向のしま模様に最も反応)に固定されており、b は未使用。方向を振りたい場合は本 op ではできないので注意。
Border handling: mirror repeating the edge pixel (d c b a | a b c d — scipy's default `reflect) (measured; tools/impl2/border_probe.py`).
Value comparability (measured): the output is normalised by that image's own maximum (the output maximum is always 1.0, and scaling the input leaves the output unchanged). Values therefore cannot be compared across images — a feature of the same strength takes a different value depending on what the strongest feature in that image happens to be, and in an image holding only weak features the noise is lifted to 1.0. To compare across images, rescale by a common reference.
• gallery2d_texture_freq family guide
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
sk_gabor 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
texture)std_filter · local_bimodality · local_std · scale_select_std · bootstrap_std_error · structure_tensor_orientation · structure_tensor_coherence · gabor
*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.